- Why data viz?
- Types of viz
- Best practices
- What to watch for when reading viz or avoid when creating viz
Communicating data
Data analysts use it in every step of the data analysis workflow:
Tables of numbers can be used for those similar purposes, often effectively. Viz can often convey the most important information more quickly and easily
Often relative relationships are more important than exact numbers
geom_text)Some relationships are difficult to express in a table
date new_cases 2020-09-01 41667 2020-09-02 40940 2020-09-03 44085 2020-09-04 50415 2020-09-05 42982 2020-09-06 31299 2020-09-07 23468 2020-09-08 27435 2020-09-09 33754 2020-09-10 36120 2020-09-11 47649 2020-09-12 41077
No obvious trends.
date away home attendance 2017-04-02 SFN ARI 49016 2017-04-02 CHN SLN 47566 2017-04-02 NYA TBA 31042 2017-04-03 PHI CIN 43804 2017-04-03 SDN LAN 53701 2017-04-03 COL MIL 43336 2017-04-03 ATL NYN 44384 2017-04-03 MIA WAS 42744 2017-04-03 TOR BAL 45667 2017-04-03 PIT BOS 36594 2017-04-03 SEA HOU 41678 2017-04-03 KCA MIN 39615
No obvious weekly trends.
Use color to show magnitude of numeric data over 2 dimensions
Consider the audience and platform. May want different versions depending on the audience/platform/medium.
Audience
Platform
Viz with no clear takeaway
Note: 5% of the population (mostly male) is Red-Green colorblind
Want the option of more information, but don’t want to clutter the viz.Â
Show information on hover
Want to show trends in data over time, but line plot is too simple.
Example: Player and ball locations over time, 25 times a second. Impossible to process by looking at the data set.
Visualization is for understanding and communicating data, and it ideally
does those
and is appropriate for
What is the purpose?
Who is the audience?
In what context will they see this visualization?
What is the key observation or takeaway?
Does the visualization have unnecessary features that distract from the main takeaway?